Fragmentarium: a Model for Digital Fragmentology

Fragmentarium: a Model for Digital Fragmentology

Introduction: One of the major challenges of digital data workflows in the Arts and Humanities is that resources that belong together, in extreme cases, like this particular one, even parts of dismembered manuscripts, are hosted and embedded in different geographical and institutional silos. Combining IIIF with a mySQL database, Fragmentarium provides a user-friendly but also standardized, open workspace for the virtual reconstruction of medieval manuscript fragments. Lisa Fagin Davis’s blog post gives contextualized insights of the potentials of Fragmentarium and how, as she writes, “technology has caught up with our dreams”. 

Mining ethnicity: Discourse-driven topic modelling of immigrant discourses in the USA, 1898–1920

Mining ethnicity: Discourse-driven topic modelling of immigrant discourses in the USA, 1898–1920

Introduction: The article illustrates the application of a ‘discourse-driven topic modeling’ (DDTM) to the analysis of the corpus ChronicItaly comprising several newspapers in Italian language, appeared in the USA during the time of massive migration towards America between the end of the XIX century and the first two decades of the XX (1898-1920).

The method combines both Text Modelling (™) and the discourse-historical approach (DHA) in order to get a more comprehensive representation of the ethnocultural and linguistic identity of the Italian group of migrants in the historical American context in crucial periods of time like that immediately preceding the eruption and that of the unfolding of World War I.

Analyzing Documents with TF-IDF | Programming Historian

Analyzing Documents with TF-IDF | Programming Historian

Introduction: The indispensable Programming Historian comes with an introduction to Term Frequency – Inverse Document Frequency (tf-idf) provided by Matthew J. Lavin. The procedure, concerned with specificity of terms in a document, has its origins in information retrieval, but can be applied as an exploratory tool, finding textual similarity, or as a pre-processing tool for machine learning. It is therefore not only useful for textual scholars, but also for historians working with large collections of text.